IL299173B1 - Fragrance ingredient spatial recognisability prediction methods and fragrance composition spatial recognisability prediction methods - Google Patents
Fragrance ingredient spatial recognisability prediction methods and fragrance composition spatial recognisability prediction methodsInfo
- Publication number
- IL299173B1 IL299173B1 IL299173A IL29917322A IL299173B1 IL 299173 B1 IL299173 B1 IL 299173B1 IL 299173 A IL299173 A IL 299173A IL 29917322 A IL29917322 A IL 29917322A IL 299173 B1 IL299173 B1 IL 299173B1
- Authority
- IL
- Israel
- Prior art keywords
- ingredient
- minimum
- value
- fragrance
- distance
- Prior art date
Links
- 239000004615 ingredient Substances 0.000 title claims 59
- 239000003205 fragrance Substances 0.000 title claims 34
- 239000000203 mixture Substances 0.000 title claims 17
- 238000000034 method Methods 0.000 title claims 14
- 230000001953 sensory effect Effects 0.000 claims 21
- 238000010790 dilution Methods 0.000 claims 17
- 239000012895 dilution Substances 0.000 claims 17
- 239000012071 phase Substances 0.000 claims 14
- 231100000673 dose–response relationship Toxicity 0.000 claims 5
- 239000007791 liquid phase Substances 0.000 claims 5
- 238000004088 simulation Methods 0.000 claims 2
- 239000012530 fluid Substances 0.000 claims 1
- 238000002360 preparation method Methods 0.000 claims 1
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
- G16C20/30—Prediction of properties of chemical compounds, compositions or mixtures
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C60/00—Computational materials science, i.e. ICT specially adapted for investigating the physical or chemical properties of materials or phenomena associated with their design, synthesis, processing, characterisation or utilisation
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01L—CHEMICAL OR PHYSICAL LABORATORY APPARATUS FOR GENERAL USE
- B01L5/00—Gas handling apparatus
- B01L5/02—Gas collection apparatus, e.g. by bubbling under water
Landscapes
- Engineering & Computer Science (AREA)
- Computing Systems (AREA)
- Theoretical Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Chemical & Material Sciences (AREA)
- Crystallography & Structural Chemistry (AREA)
- Health & Medical Sciences (AREA)
- Clinical Laboratory Science (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Fats And Perfumes (AREA)
- Disinfection, Sterilisation Or Deodorisation Of Air (AREA)
- Cosmetics (AREA)
Claims (11)
1. Fragrance ingredient or composition spatial recognisability prediction method (200, 300, 400, 500, 1000) to prepare a fragrance composition comprising said fragrance ingredient or composition, 5 comprising the steps of: - selecting (205, 305, 410, 1005), upon a computer interface, a value representative of between one or two of the following parameters: - a minimum sensory intensity level, corresponding to a predetermined minimum psychophysical intensity for the ingredient, 10 - a maximum distance, corresponding to a distance at which the ingredient is to be perceived at a minimum predetermined psychophysical intensity level or - a quantity of the ingredient in liquid phase, wherein the selected value is selected within a range of at least two distinct values, - computing (215, 315, 1020), by a computing system, a value representative of either one of the 15 following parameters: - a minimum sensory intensity level, corresponding to a predetermined minimum psychophysical intensity for the ingredient, - a maximum distance, corresponding to a distance at which the ingredient is to be perceived at a minimum sensory intensity level selected or set by default, or 20 - a quantity of the ingredient in liquid phase and wherein the computed value is representative of a parameter other than the parameter associated with the selected value and wherein a value for the parameter neither selected nor computed is set to a default value, said computed value being computed as a function of the parameter associated with the selected value and the value for the parameter neither selected nor computed, an ingredient being 25 represented by an ingredient digital identifier corresponding to a physical ingredient to be used within a fragrance composition to be prepared as a function of the computed and selected values.
2. Fragrance ingredient or composition spatial recognisability prediction method (200) according to claim 1, comprising the steps of: 30 - selecting (205), upon a computer interface, a value representative of a minimum requested sensory intensity level, corresponding to a desirable predetermined perceived minimum 299173/2 51 psychophysical intensity for the ingredient, said value being selected within a range of at least two distinct values, - determining (240), by a computing system, a value representative of a minimum gas phase concentration of the ingredient corresponding to the selected minimum sensory intensity level as 5 a function of a dose-response curve linking gas phase concentration to the selected minimum sensory intensity, - calculating (210), by a computing system, a maximum total acceptable ingredient dilution, for both in gas and liquid phases of the fragrance, as a function of the determined minimum gas phase concentration and 10 - computing (215), by a computing system, at least one value representative of a distance from the fragrance source, up to a maximum distance from the fragrance source, at which the ingredient presents at least the minimum sensory intensity level selected as a function of the maximum total ingredient dilution calculated, said computing step comprising a step of retrieving (220), from an electronic storage, at least one value representative of the minimum spatial dilution for an 15 ingredient in the gas phase corresponding to a predetermined downstream distance from the fragrance source.
3. Method (200) according to claim 2, which further comprises, prior to the step of retrieving (220), a step of constructing (225) a minimum spatial dilution electronic storage, said step of constructing matching 20 minimum spatial dilution values to at least one distance from a fragrance source value and at least one of the following indicators: - an indicator representative of an incoming air flow velocity incident upon the fragrance source comprising said ingredient, - an indicator representative of an ingredient or fragrance composition application surface area, 25 - an indicator representative of simulation parameters for the shape of a human body and/or - an indicator representative of area location on a human body upon which the ingredient or fragrance composition is applied, said step of constructing comprising a step of computational fluid dynamics simulation (230) configured to calculate said spatial dilution values at predetermined downstream distances from the source. 30 299173/2 52
4. Method (200) according to any one of claims 2 to 3, which further comprises a step of setting (245) a value representative of a duration of dry down of an ingredient, the step of computing (215) of a value representative of a distance from the fragrance source being achieved as a function of the duration of dry down set. 5
5. Fragrance ingredient or composition spatial recognisability prediction method (300) according to claim 1, comprising the steps of: - selecting (305), upon a computer interface, a value representative of a distance within a range of at least two distinct values and up to a maximum downstream distance from the fragrance source 10 at which the ingredient presents a minimum sensory intensity level corresponding to a predetermined minimum psychophysical intensity for the ingredient, - retrieving (310), from an electronic storage, a minimum spatial dilution value associated with the selected distance, - determining (340), by a computing system, a value representative of gas phase concentration of 15 the ingredient corresponding to the spatial dilution value retrieved and - computing (315), by a computing system, for the selected value of distance, at least one value representative of a sensory intensity level as a function of a dose-response curve linking gas phase concentration to sensory intensity level. 20
6. Fragrance ingredient or composition spatial recognisability prediction method (1000) according to claim 1, comprising the steps of: - selecting (1005), upon a computer interface, a value representative of a minimum sensory intensity level to be achieved, corresponding to a predetermined minimum psychophysical intensity for the ingredient, 25 - selecting (1006), upon a computer interface, a value representative of a downstream distance from a fragrance source, - determining (1010), by a computing system, a value representative of the gas phase concentration of the ingredient corresponding to the selected minimum sensory intensity level as a function of a dose response for said ingredient linking gas phase concentration to the selected 30 minimum sensory intensity, 299173/2 53 - retrieving (1011), from an electronic storage, a value of minimum spatial dilution as a function of the selected distance from the fragrance source, - calculating (1015), by a computing system, at least one value representative of maximum total ingredient dilution as a function of the determined gas phase concentration for said ingredient and 5 - computing (1020), by a computing system, for at least one value representative of maximum total ingredient dilution calculated and at least one value representative of minimum spatial dilution retrieved for the selected distance, at least one value representative of a quantity of ingredient in liquid phase, so that the ingredient presents the minimum sensory intensity level as a function of the value of ingredient dilution at the predetermined distance. 10
7. Fragrance composition spatial recognisability prediction method (400) according to claim 1, comprising the steps of: - electing (405), upon a computer interface, at least two ingredient digital identifiers to form a fragrance source, 15 - setting (410), upon a computer interface, a value representative of a relative quantity of at least one said ingredient identified by said digital identifier, - selecting (205), upon a computer interface, a value representative of a minimum requested sensory intensity level, corresponding to a desirable predetermined perceived minimum psychophysical intensity for at least one ingredient, said value being selected within a range of at 20 least two distinct values, - determining (240), by a computing system, a value representative of a minimum gas phase concentration for each said ingredient corresponding to the selected minimum sensory intensity level as a function of a dose-response curve linking gas phase concentration to the selected minimum sensory intensity, 25 - calculating (210), by a computing system, a maximum total ingredient dilution, for both in gas and liquid phases of the fragrance, as a function of the determined minimum gas phase concentration, for each said ingredient and - computing (215), by a computing system, at least one value representative of a distance from the fragrance source, up to a maximum distance from the fragrance source, at which at least one 30 ingredient presents at least the minimum sensory intensity level selected as a function of the maximum total ingredient dilution calculated. 299173/2 54
8. Method (400) according to claim 7, in which at least one ingredient digital identifier is associated, in a computer memory, to a descriptor representative of the scent of the corresponding ingredient, wherein the method further comprises a step of providing (415), upon a computer interface, at least one 5 alternative ingredient digital identifier to at least one of the elected ingredient digital identifiers as a function of at least one descriptor associated to said elected ingredient digital identifier.
9. Method (400) according to claim 8, in which the step of providing (415) is achieved as a function of both at least one descriptor associated to said elected ingredient digital identifier and the computed value 10 representative of a maximum downstream spatial distance for said ingredient digital identifier.
10. Fragrance composition spatial recognisability prediction method (500) according to claim 1, comprising the steps of: - electing (405), upon a computer interface, at least two ingredient digital identifiers forming a 15 fragrance source, - setting (410), upon a computer interface, a value representative of a relative quantity of at least one said ingredient identified by said digital identifier, - selecting (305), upon a computer interface, a value representative of a distance within a range of at least two distinct values and up to a maximum downstream distance from the fragrance source 20 at which at least one ingredient presents a minimum sensory intensity level corresponding to a predetermined minimum psychophysical intensity for each said ingredient, - retrieving (310), from an electronic storage, a minimum spatial dilution value associated with the selected distance, - determining (340), by a computing system, a value representative of gas phase concentration of 25 at least one said ingredient corresponding to the spatial dilution value retrieved and - computing (315), by a computing system, for the selected value of distance, at least one value representative of a sensory intensity level as a function of a dose-response curve linking gas phase concentration to sensory intensity level. 30
11. Fragrance (1300) composition preparation method, characterised in that it comprises: 299173/2 55 - a step (1305) of selecting, upon a computer interface, at least one ingredient digital identifier to form a fragrance composition digital representation, - a step (1310) of predicting, by a computing device, a spatial recognisability for at least one selected ingredient digital identifier according to a fragrance composition spatial recognisability 5 prediction method according to any one of claims 1 to 10 and - a step (1315) of preparing a fragrance composition as a function of the fragrance composition digital representation.
Applications Claiming Priority (5)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US202063085183P | 2020-09-30 | 2020-09-30 | |
| EP20208016 | 2020-11-17 | ||
| US202163134449P | 2021-01-06 | 2021-01-06 | |
| US202163175635P | 2021-04-16 | 2021-04-16 | |
| PCT/EP2021/076950 WO2022069634A1 (en) | 2020-09-30 | 2021-09-30 | Fragrance ingredient spatial recognisability prediction methods and fragrance composition spatial recognisability prediction methods |
Publications (3)
| Publication Number | Publication Date |
|---|---|
| IL299173A IL299173A (en) | 2023-02-01 |
| IL299173B1 true IL299173B1 (en) | 2023-12-01 |
| IL299173B2 IL299173B2 (en) | 2024-04-01 |
Family
ID=77999006
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| IL299173A IL299173B2 (en) | 2020-09-30 | 2021-09-30 | Fragrance ingredient spatial recognisability prediction methods and fragrance composition spatial recognisability prediction methods |
Country Status (7)
| Country | Link |
|---|---|
| US (1) | US20230253075A1 (en) |
| EP (2) | EP4143833A1 (en) |
| JP (1) | JP7438410B2 (en) |
| CN (1) | CN115803818A (en) |
| BR (1) | BR112022024313A2 (en) |
| IL (1) | IL299173B2 (en) |
| WO (1) | WO2022069634A1 (en) |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH08127522A (en) * | 1994-10-28 | 1996-05-21 | Pola Chem Ind Inc | Evaluation of perfumery composition |
| US20070071780A1 (en) | 2005-06-16 | 2007-03-29 | Dubois Zerlina G | Personal care composition comprising a perfume booster accord |
| US20150284660A1 (en) | 2012-08-21 | 2015-10-08 | Firmenich Sa | Method to improve the performance of encapsulated fragrances |
| GB201409348D0 (en) | 2014-05-27 | 2014-07-09 | Givaudan Sa | Perfume compositions |
| GB201721558D0 (en) | 2017-12-21 | 2018-02-07 | Givaudan Sa | Method of creating an organic composition |
-
2021
- 2021-09-30 WO PCT/EP2021/076950 patent/WO2022069634A1/en active Application Filing
- 2021-09-30 CN CN202180046307.3A patent/CN115803818A/en active Pending
- 2021-09-30 US US18/003,149 patent/US20230253075A1/en active Pending
- 2021-09-30 JP JP2022577411A patent/JP7438410B2/en active Active
- 2021-09-30 EP EP21782761.7A patent/EP4143833A1/en active Pending
- 2021-09-30 BR BR112022024313A patent/BR112022024313A2/en not_active Application Discontinuation
- 2021-09-30 EP EP24181911.9A patent/EP4421813A2/en active Pending
- 2021-09-30 IL IL299173A patent/IL299173B2/en unknown
Also Published As
| Publication number | Publication date |
|---|---|
| WO2022069634A1 (en) | 2022-04-07 |
| IL299173B2 (en) | 2024-04-01 |
| IL299173A (en) | 2023-02-01 |
| EP4143833A1 (en) | 2023-03-08 |
| US20230253075A1 (en) | 2023-08-10 |
| BR112022024313A2 (en) | 2023-04-18 |
| JP2023541499A (en) | 2023-10-03 |
| EP4421813A2 (en) | 2024-08-28 |
| CN115803818A (en) | 2023-03-14 |
| JP7438410B2 (en) | 2024-02-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Wisselink et al. | 3D FEM simulation of stationary metal forming processes with applications to slitting and rolling | |
| Ma et al. | Modeling the complex dynamics of derecruitment in the lung | |
| CN109829971B (en) | Method and device for creating human body virtual model | |
| JP2013502659A5 (en) | ||
| WO2006084845A3 (en) | Processor-simulation method using a model comprising a set of objects | |
| JPWO2012173283A1 (en) | System performance prediction method, information processing apparatus and control program thereof | |
| IL299173B1 (en) | Fragrance ingredient spatial recognisability prediction methods and fragrance composition spatial recognisability prediction methods | |
| Pugliese et al. | A simple model of pathogen–immune dynamics including specific and non-specific immunity | |
| CN107451321A (en) | A kind of pilot's cardiorespiratory system emulation modelling method for being used to block warship process | |
| Drama et al. | Postural stability in human running with step-down perturbations: an experimental and numerical study | |
| CN106506564B (en) | Vulnerability management method and device | |
| EP4295258A1 (en) | Method for ascertaining the charge state of a phase-change material | |
| Wang et al. | A hybrid shallow water approach with unstructured triangular grids for urban flood modeling | |
| KR102090596B1 (en) | Optimum design method for fluid system | |
| CN109740192A (en) | Crowd evacuation emulation method and system based on Arnold mood model | |
| Scase et al. | Boussinesq plumes and jets with decreasing source strengths in stratified environments | |
| Foster et al. | Application of benchmark dose risk assessment methodology to developmental toxicity: an industrial view | |
| CN106485028B (en) | Support the flexible body deformation simulation modeling method pressed in real time | |
| Boudier et al. | Coupling a thermal comfort model with building simulation for user comfort and energy efficiency | |
| CN108826597A (en) | Control method and device of air conditioning equipment | |
| CN109282961A (en) | A kind of power transmission tower gas elastic model parameter regulation means and device | |
| CN118361830B (en) | Bluetooth WiFi temperature and humidity controller control method based on environment sensing | |
| Li et al. | The study of neural network in the application of pmv index | |
| JP2022062690A (en) | Modeling and simulation of material microstructure | |
| Nagata | A simple method to incorporate thermal bridge effects into dynamic heat load calculation programs |